Where do things go wrong with inspection reports?
An inspector assesses a batch, fills in a report on paper or in a PDF template supplied by the vendor, and sends it in. Someone in the office then types the inspection results into the quality system or the ERP. That is the pain point: the inspector has already done the work, but the data is not yet where it needs to be. On top of that, these reports never arrive in a single fixed format. One supplier sends an Excel file, another a scanned handwritten note, a third a PDF with its own layout. Setting up a template for each sender means weeks of work before the first report flows through automatically.
What does dottle specifically solve when automating inspection reports?
dottle reads the incoming report, recognises the relevant fields (batch number, inspection result, deviations, date, supplier) and delivers them as structured data to the system where quality administration is maintained. This works without configuring a template per sender: dottle understands the document context rather than looking for a fixed position on the page. A staff member approves the extracted values before they are written to the system. Deviations are flagged, not silently passed through. Quality control stays with the person; the retyping disappears.
How does this differ from standard OCR or scan-and-recognise?
Standard OCR recognises text and returns a block of raw characters. That is useful for making an archive searchable, but it does not solve the data-entry problem. After the scan you know that somewhere on the page it says '4.2 kg deviation class B', but your system does not. dottle goes one step further: it links the recognised value to the correct field, matches the report to the right batch or order in your system, and makes the data immediately usable. The difference is comparable to the difference between a photo of a receipt and a posted invoice.
When is automating inspection reports not the right choice?
There are three situations in which it is better not to start. First: when volume is too low. A handful of reports per week can be retyped by a staff member in fifteen minutes; the setup and maintenance cost more than they save. Second: when the inspection process itself is not yet stable. If the fields you record change every month, or if the definition of a deviation has not been settled, you are automating a process that needs to be streamlined first. Third: when the source documents are structurally unreadable, think handwritten reports with corrections, illegible handwriting, or incomplete information. Automation handles good documents quickly; poor documents remain poor documents.
What trade-offs should you account for?
The biggest trade-off is attention at the start. dottle goes live in two weeks, but during those two weeks you need to know which fields you want to capture and where they need to go in your system. Anyone who is unclear on that will get stuck halfway through the setup. A second point: new document formats that have not been seen before are added in a controlled way. This is not an automatic learning process but a deliberate choice, so that the output remains predictable. For organisations that onboard many new suppliers, this means a small amount of maintenance time per new format. At high volume that easily outweighs the alternative, but it is fair to state this upfront.